To overcome the issue mentioned above, it is a need to come up with a real-time approach that maintains a good accuracy on point-wise classification. Inspired by the Voxelization in VoxelNet [1]}, the same approach was followed to represent a LiDAR point cloud as a voxel Grid map, where points on both x and y are discretized with a certain resolution as done in bird-eye view projection while LiDAR layers are represented in the height as they are. This produces a volumetric bird-eye view shape maintaining all the height information in order not to lose those features. The number of layers in LiDAR can be known in advance and so does the height as the third dimension. This volumetric map is further used as an input to a 2D segmentation network, where the third dimension(layers) is used as input channels.
